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Record W2577803396 · doi:10.1128/msphere.00340-16

Optimized CRISPR-Cas9 Genome Editing for <i>Leishmania</i> and Its Use To Target a Multigene Family, Induce Chromosomal Translocation, and Study DNA Break Repair Mechanisms

2017· article· en· W2577803396 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuemSphere · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsMcGill University
FundersCanadian Institutes of Health ResearchGovernment of Canada
KeywordsBiologyCRISPRGenome editingCas9GeneticsGeneGuide RNARecombinaseHomologous recombination

Abstract

fetched live from OpenAlex

Leishmania parasites cause human leishmaniasis. To accelerate characterization of Leishmania genes for new drug and vaccine development, we optimized and simplified the CRISPR-Cas9 genome-editing tool for Leishmania . We show that co-CRISPR targeting of the miltefosine transporter gene and serial transfections of an oligonucleotide donor significantly eased isolation of edited mutants. This cotargeting strategy was efficiently used to delete all 11 members of the A2 virulence gene family. This technical advancement is valuable, since there are many gene clusters and supernumerary chromosomes in the various Leishmania species and isolates. We simplified this CRISPR system by developing a gRNA and Cas9 coexpression vector which could be used to delete genes in various Leishmania species. This CRISPR system could also be used to generate specific chromosomal translocations, which will help in the study of Leishmania gene expression and transcription control. This study also provides new information about double-strand DNA break repair mechanisms in Leishmania .

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.099
Threshold uncertainty score0.924

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.293
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it